Fast and efficient terrain-aware motion planning for exploration rovers

Title Fast and efficient terrain-aware motion planning for exploration rovers
Author Uğur, Deniz, Bebek, Özkan
Publication Date: 2021
Publication Place - IEEE
Type Document
Language English
Digital Yes
Manuscript No
Library: Özyeğin University
Library Asset ID 978-166541873-7
Record ID fcb85101-37fa-4736-9963-d5010d9ce3b4
Library Location Mechanical Engineering
Date 2021
Notes Ozyegin University
Sample Text This paper presents a fast, energy-efficient, and low computational cost traversal solution on sloped terrain. The use of grid-based search algorithms requires high computational power and takes a long time because almost every point on the map is visited. An approach that does not depend on the global map but can also navigate towards the target can be presented as a new solution. A cost map for motion planning using depth field and color image data is formed in real-time. The proposed motion planning algorithm, named SAFARI, utilizes four cost layers to efficiently evaluate its surroundings. To reduce the computational overhead, only select features are evaluated and the rover's motion planning cycle speed is increased. SAFARI has been tested against path planning alternatives and has also been proven to work with simulations and field tests. This concept is expected to be used in space applications and cave exploration tasks.
DOI 10.1109/CASE49439.2021.9551617
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Fast and efficient terrain-aware motion planning for exploration rovers

Author Uğur, Deniz, Bebek, Özkan
Publication Date 2021
Publication Place - IEEE
Type Document
Language English
Digital Yes
Manuscript No
Library Özyeğin University
Library Asset ID 978-166541873-7
Record ID fcb85101-37fa-4736-9963-d5010d9ce3b4
Library Location Mechanical Engineering
Date 2021
Notes Ozyegin University
Sample Text This paper presents a fast, energy-efficient, and low computational cost traversal solution on sloped terrain. The use of grid-based search algorithms requires high computational power and takes a long time because almost every point on the map is visited. An approach that does not depend on the global map but can also navigate towards the target can be presented as a new solution. A cost map for motion planning using depth field and color image data is formed in real-time. The proposed motion planning algorithm, named SAFARI, utilizes four cost layers to efficiently evaluate its surroundings. To reduce the computational overhead, only select features are evaluated and the rover's motion planning cycle speed is increased. SAFARI has been tested against path planning alternatives and has also been proven to work with simulations and field tests. This concept is expected to be used in space applications and cave exploration tasks.
DOI 10.1109/CASE49439.2021.9551617
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